What this category’s data looks like
Production data for this category typically originates from order design systems, sheet material and wood batch ledgers, CNC cutting and drilling equipment, ERP/MES systems, and moisture content testing equipment. Data update frequency shifts based on orders, batches, or daily cycles. Common daily documents include order breakdown drawings, cutting lists, edge banding and drilling programs, coating process documents, hardware detail lists, and trial assembly and packaging records. Document structures mix structured tables, text paragraphs, and embedded code. Fields include panel specifications, material batch numbers, process parameters, hardware models, and more. Some documents include unit labels such as millimeters and kilograms.
Constraints on document parsing and chunking workflows
This category features diverse document types and complex structures, mixing text, tables, and CNC program code. Chunking rules must support content extraction across different formats. Custom order-driven production models result in large document volumes per batch and numerous panel details. Chunking must balance context completeness and retrieval efficiency, to avoid losing business associations between panels and their corresponding batches. Data update frequency varies with orders and batches, so reasonable timeout parameters must be configured for high-frequency parsing tasks. The accuracy of core fields directly impacts subsequent ledger summarization. Chunking must retain associations between fields, to prevent critical information from being broken apart during splitting.
How to set the configurations
These configurations are based on FastGPT v4.17.0:
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | This category’s documents contain large numbers of structured fields like panel dimensions and hardware details. This range preserves complete business associations for a single panel group or single list |
chunkSplitter | Split by paragraph + table boundaries | This category’s documents mix text paragraphs, process tables, and order breakdown lists. Splitting by boundaries avoids chunking across business units |
customPdfParse | Enabled | This category’s documents contain CNC program code and text embedded in order breakdown drawings. Enabling custom parsing extracts structured data from non-standard PDFs |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Parsing multiple documents per batch requires processing large volumes of panel data. This duration covers standard parsing tasks |
chunkSettingMode | Manual configuration | This category’s documents have large structural differences. Manual configuration adapts to different types of production ledger documents |
UPLOAD_FILE_MAX_SIZE | 1000 MB | A single batch’s production ledgers may include multiple cutting lists and order breakdown drawings. This upper limit supports bulk upload requirements |
Three common misconfigurations
- Symptom: After uploading a complete production ledger PDF, core panel dimension and hardware detail fields cannot be retrieved. Cause:
customPdfParseis not enabled, so embedded CNC program code and text in order breakdown drawings interfere with accurate extraction of structured fields. - Symptom: After uploading multiple production documents, the generated summary report only includes content from some of the cutting lists. Cause:
chunkSizeis set too small, splitting a single complete cutting list into multiple independent chunks, leading to loss of business associations between panel specifications and their corresponding batch numbers. - Symptom: Parsing a batch of order breakdown drawing files fails directly with a timeout. Cause:
PARSE_FILE_TIMEOUT_SECONDSis set too short, failing to cover the actual time required for bulk multi-document parsing.
How to confirm configurations are correct
- Upload a typical cutting list PDF, review parsed text content, and confirm core fields such as panel dimensions and batch numbers are fully extracted.
- Manually adjust the value of
chunkSize, upload the same document to compare chunking results, and confirm chunks retain the integrity of single sets of business data. - Upload bulk production documents, check task status and parsing logs, and confirm no timeout or upload block prompts appear.
- Initiate a retrieval against the configured knowledge base, and verify that retrieval results for core business fields meet expectations.
The values provided are common starting points, and should be evaluated against the user’s own samples.